The present invention relates to the field of wireless cellular networks, more specifically to an approach for controlling operation within a cell of a wireless cellular network, to a base station of such a wireless cellular network and to a wireless cellular network, wherein the approach allows controlling operation within the cell on the basis of information only locally available in the cell.
Wireless communication systems are moving towards heterogeneous architectures, as it is for example described in reference [1]. In such architecture within a cell a user may have different types of access points (APs), for example, as is described in reference [1] four different types of access points, like macro-, pico-, femto-cells, relays and/or remote radio heads. Basically, this may provide many positive effects for a mobile station (MS), which can now choose among several connections to find the most suitable one. However, for example femto-cellular overlays provide many difficulties and challenges, for example, with regard to the cell-organization/optimization, the resource assignment to users and, especially, the interference coordination between access points within the same cell and one or more neighboring cells.
FIG. 1 shows a schematic representation of an exemplary heterogeneous network, more specifically a densely deployed HetNet scenario. FIG. 1 shows a cell 100 of a wireless cellular network. The cell 100 comprises a base station BS serving a plurality of mobile stations MS1 and MS2 within the cell 100. The cell 100 includes three sectors 1011 to 1013, and mobile station MS1 is in sector 1001, and mobile station MS2 is located in sector 1003. FIG. 1 further shows relay stations RS1 in sector 1001 and RS2 in sector 1003. The relay stations serve an area within the respective sectors as it is indicated by the shaded portion around them. In addition, the cell 100 comprises two pico-cells PC1 and PC2 in sectors 1001 and 1002, respectively. Again, the area served by the pico-cells PC1 and PC2 is indicated by the shaded area around the base stations (depicted by respective antennas) of the pico-cells. Further, the cell 100 comprises femto-cells FC1 to FC4, wherein each of the sectors includes at least one of the femto-cells. In the example depicted in FIG. 1, mobile station MS1 in sector 1001 is served by the relay station RS1, as is indicated by the arrow A1. Mobile station MS2 in sector 1003 is served by the base station BS of the cell 100 as is indicated by arrow A2. In addition, in a cell 100 as it is depicted in FIG. 1, the respective mobile stations may experience also interference from other radio sources. Exemplary sources for interference with the mobile station MS1 are the base station BS and the pico-cell PC1, as indicated by arrows I1 and I2. In sector 1003 the relay station RS2 and the femto-cell FC3 are assumed to be a source of interference for mobile station MS2, as is indicated by arrows 13 and 14.
In view of the various types, locations and densely deployment of access points, like the relay stations, the pico-cells and the femto-cells as depicted in FIG. 1, and due to the different transmission powers/ranges associated therewith, numerous technical challenges are posed, for example by femto/pico-cell overlays, as it is described in detail in references [1], [2] or [3]. Basically, these challenges fall into the following areas:                Network self-organization: self-configuration, -healing, and -optimization are necessitated for all cells. These tasks become increasingly difficult given the additional number of network parameters that need to be considered in an environment as it is schematically depicted in FIG. 1.        Backhauling: the connections of different base stations to the core-network necessitate additional infrastructure, however, in case of femto-cells it is not possible to guarantee a connection through the user's DSL line thereby leaving the user without connection to the backhaul system.        Handover: the higher number of access points increases the amount of handover decisions to be made within the network.        Interference: cross-tier interference will be created to/from the overlaid cells, for example, the pico/femto-cells shown in FIG. 1. This interference has to be mitigated to maintain performance, especially, in case access to the cells is restricted, as in such a situation also the high intra-femto-tier interference due to the dense deployment is of concern.        
The handling of interference within and across tiers is paramount to the performance of a wireless network, and the main sources of interference in densely deployed femto-cell scenarios (see reference [1]) can be categorized and broken down as follows:                Unplanned deployment:        Low-power nodes, e.g., femto-cells, are deployed by end users at “random” locations, and can be active or inactive at any time thereby further randomizing the possible interference.        In view of the backhauling difficulty (such as a non-operator DSL connection), the interference coordination with the femto-cells may not be possible.        A continuous sensing and monitoring is necessitated by the cells to dynamically/adaptively mitigate interference from the other tiers.        Inter-tier interference needs to be considered due to the densely deployed femto-cells.        Closed-subscriber access:        Restricted access control of pico- and femto-cells may lead to strong interference scenarios both in the uplink and downlink, in case the user cannot carry out a handover.        This will cause large interference at the mobile stations that are near femto-cells or pico-cells but cannot access these cells (see arrows I2 and I4 in FIG. 1).        Node transmission power differences:        The low power of nodes of pico- and femto-cells may cause an association issue and also downlink/uplink interference problems, for example, a mobile station near a pico-cell connected (in the downlink) to a high power macro-base station may cause a large uplink interference at the pico-cell        
For addressing interference issues, in the art, standard inter-cell interference coordination techniques (ICIC techniques) are known, however, these ICIC techniques utilize a centralized approach, and mainly deal with macro-to-macro or small cell-to-macro interference reduction, as is described in references [1], [2] and [3]. However, as outlined above, in a scenario as it is schematically depicted in FIG. 1, there is no guarantee for a backhaul connection between the different access points so that such schemes, without guarantee of backhaul connections between the different access points, are ineffective.
In references [4] and [5] downlink power control mechanisms are suggested to prevent large co-channel interference (CCI) from a femto-cell base station at nearby macro-users (see for example femto-cell FC3 in FIG. 1). In reference [4], the downlink power control problem is formulated to address CCI, while the quality of service requirements for both the macro- and femto-users are taken into account. This is in contrast to reference [5] in accordance with which macro-cell users are given priority. In this approach, a listening time-division duplex frame is utilized to estimate the channel quality information of the surrounding macro-users, and to adjust the femto-cell base station downlink transmit power accordingly. References [4] and [5] both deal with interference reduction to the macro-cell in the downlink, whereas the femto-femto interference issue is disregarded.
Reference [6] chooses a game theoretic approach to manage downlink interference between femto-cells and the macro-cells. A proportional fair metrical use to minimize interference and improve throughput fairness, however, the overall system throughput suffers. A further proposal for addressing the uplink power control problem is described in reference [7] and uses conventional and/or fractional power control. These procedures, however, are developed for the macro-cellular environment, and do not guarantee quality of service.
For enhancing the throughput in a wireless cellular network, fractional frequency reuse (FFR) may be used, and in accordance with this approach, in a wireless cellular network, the throughput of cell-edge users is enhanced by allocating orthogonal resources in neighboring cells. However, because FFR decreases the spatial reuse of resources, the system capacity inherently suffers. Additionally, the unpredictable variations of the interference environment caused by the uncoordinated deployment of femto-cells necessitates a dynamic interference reuse approach aiming at adapting the spatial reuse of the radio sources to the observed interference conditions. Dynamic frequency reuse may be leveraged by a central approach or by a distributed approach. Assigning resources to the base stations by means of a central controller achieves a more efficient resource utilization, at the expense of higher complexity in the network infrastructure and additional signaling. In a distributed approach, where each base station autonomously carries out the resource allocation, as it is, for example, described in references [8] to [12] the base stations may individually access a predefined number of subbands, however, this greatly restricts the possibility of a subband reassignment in case the interference conditions change.
In Long-Term Evolution (LTE)-Advanced (LTE-A), a carrier aggregation is utilized. Multiple blocks of LTE bandwidth, named component carriers (CCs), are merged to obtain a broader usable spectrum, as is described in references [13] and [14]. This carrier aggregation provides an additional degree of freedom which can be exploited in interference mitigation techniques, for example by optimizing the selection of subsets of available CCs among the contending base stations. In references [15] to [17] CC selection schemes relying on the interference environment of base stations in an LTE-A system are described, however, these approaches result in excessive signaling between the base stations and do not offer any explicit protection of cell-edge mobile stations in densely deployed uncoordinated networks.